---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_beit_base_adamax_001_fold2
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5777777777777777
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_5x_beit_base_adamax_001_fold2

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 6.3078
- Accuracy: 0.5778

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4226        | 1.0   | 27   | 1.4140          | 0.2667   |
| 1.2045        | 2.0   | 54   | 1.6573          | 0.2889   |
| 1.2481        | 3.0   | 81   | 1.5730          | 0.2889   |
| 1.322         | 4.0   | 108  | 1.5814          | 0.2889   |
| 0.9418        | 5.0   | 135  | 1.4941          | 0.4889   |
| 0.9982        | 6.0   | 162  | 1.2480          | 0.4222   |
| 0.9049        | 7.0   | 189  | 1.2328          | 0.4667   |
| 0.7944        | 8.0   | 216  | 1.2343          | 0.4889   |
| 0.9595        | 9.0   | 243  | 1.3356          | 0.4667   |
| 0.7289        | 10.0  | 270  | 1.3692          | 0.4889   |
| 0.696         | 11.0  | 297  | 1.4324          | 0.4444   |
| 0.7466        | 12.0  | 324  | 1.4783          | 0.4667   |
| 0.7646        | 13.0  | 351  | 1.3725          | 0.4889   |
| 0.6451        | 14.0  | 378  | 2.0057          | 0.5333   |
| 0.5784        | 15.0  | 405  | 2.4024          | 0.4444   |
| 0.5544        | 16.0  | 432  | 2.4151          | 0.5111   |
| 0.563         | 17.0  | 459  | 1.9054          | 0.5556   |
| 0.5213        | 18.0  | 486  | 3.0169          | 0.5333   |
| 0.551         | 19.0  | 513  | 2.4504          | 0.5333   |
| 0.613         | 20.0  | 540  | 2.7289          | 0.5333   |
| 0.4577        | 21.0  | 567  | 2.8661          | 0.5111   |
| 0.3823        | 22.0  | 594  | 2.7689          | 0.4444   |
| 0.3921        | 23.0  | 621  | 3.3303          | 0.5556   |
| 0.3974        | 24.0  | 648  | 3.5099          | 0.4444   |
| 0.3186        | 25.0  | 675  | 2.8023          | 0.5556   |
| 0.2983        | 26.0  | 702  | 3.0145          | 0.4889   |
| 0.2885        | 27.0  | 729  | 3.6675          | 0.4667   |
| 0.1902        | 28.0  | 756  | 3.2605          | 0.5556   |
| 0.2253        | 29.0  | 783  | 4.9420          | 0.5111   |
| 0.1963        | 30.0  | 810  | 4.0120          | 0.4889   |
| 0.1797        | 31.0  | 837  | 4.7762          | 0.5778   |
| 0.1892        | 32.0  | 864  | 4.0878          | 0.5333   |
| 0.1404        | 33.0  | 891  | 4.6569          | 0.5111   |
| 0.0882        | 34.0  | 918  | 4.6823          | 0.5556   |
| 0.1578        | 35.0  | 945  | 5.1512          | 0.5111   |
| 0.0782        | 36.0  | 972  | 5.2444          | 0.5778   |
| 0.0461        | 37.0  | 999  | 5.0650          | 0.5556   |
| 0.0253        | 38.0  | 1026 | 5.4464          | 0.5556   |
| 0.0617        | 39.0  | 1053 | 5.7436          | 0.5778   |
| 0.0131        | 40.0  | 1080 | 6.2467          | 0.5556   |
| 0.0373        | 41.0  | 1107 | 6.5043          | 0.5778   |
| 0.0018        | 42.0  | 1134 | 6.2715          | 0.5778   |
| 0.0403        | 43.0  | 1161 | 6.0713          | 0.5556   |
| 0.0098        | 44.0  | 1188 | 6.6508          | 0.5556   |
| 0.0159        | 45.0  | 1215 | 6.4236          | 0.5778   |
| 0.0031        | 46.0  | 1242 | 6.3525          | 0.5778   |
| 0.007         | 47.0  | 1269 | 6.2593          | 0.5778   |
| 0.0011        | 48.0  | 1296 | 6.3063          | 0.5778   |
| 0.0085        | 49.0  | 1323 | 6.3078          | 0.5778   |
| 0.0126        | 50.0  | 1350 | 6.3078          | 0.5778   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0